EF_Activities

Hands-on activities associated with the Ecological Forecasting book and graduate class

Book: Dietze, M. 2017. Ecological Forecasting. Princeton University Press https://ecoforecast.org/book

List of activities by Chapter:

Chapter 1: Introduction

• Exercise 01 - R primer

Chapter 2: From Models to Forecasts

• Exercise 02 - From models to forecasts

Chapter 3: Data, Large and Small

• Exercise 03 - Tools for working with data

Chapter 4: Scientific Workflows and the Informatics of Model-Data Fusion

• Exercise 04 - Pair Coding and Github

Chapter 5: Introduction to Bayes

• Exercise 05 - JAGS primer

• Exercise 05B - Bayesian Regression

Chapter 6:Characterizing Uncertainty

• Chapter 06 - Fitting Uncertainties

• Chapter 06 - Hierarchical Bayes

Chapter 8: Latent Variables and State-Space Models

• Exercise 06 - State Space models

Chapter 9: Fusing Data Sources

• Exercise 07 - Fusing time-series data

Chapter 11: Propagating, Analyzing, and Reducing Uncertainty

• Chapter 11 - Uncertainty Propagation and Analysis

Chapter 13: Data Assimilation 1: Analytical Methods

• Exercise 09 - Kalman Filter

Chapter 14: Data Assimilation 2: Monte Carlo Methods

• Exercise 10 - Particle Filter

Chapter 16: Assessing Model Performance

• Exercise 11 - Model Assessment

Chapter 17: Projection and Decision Support

• Exercise 12 - Decision Support

In addition this repository contains the following folders:

• data - Data files used in the exercises
• images - Image files embedded in the exercises
• tutorial - Additional tutorials contributed by previous students

For a list of Git and Github tutorials see http://gist.github.com/Pakillo/63c15c700c9c76fe8032